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| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/reachrkr/250eaf10b6252b6a936d9abcb67efcca/phi2-faiss-llamaindex_rag.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!pip install -q pypdf\n", | |
| "!pip install -q python-dotenv\n", | |
| "!pip install -q llama-index\n", | |
| "!pip install -q gradio\n", | |
| "!pip install einops\n", | |
| "!pip install accelerate\n", | |
| "!pip install faiss-cpu\n", | |
| "!pip install faiss-gpu" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 687 | |
| }, | |
| "id": "3kiH95SuTwGc", | |
| "outputId": "f1d15434-b402-40ad-f43d-329e4df3b289" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Requirement already satisfied: einops in /usr/local/lib/python3.10/dist-packages (0.7.0)\n", | |
| "Requirement already satisfied: accelerate in /usr/local/lib/python3.10/dist-packages (0.25.0)\n", | |
| "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate) (1.23.5)\n", | |
| "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (23.2)\n", | |
| "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n", | |
| "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from accelerate) (6.0.1)\n", | |
| "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (2.1.0+cu121)\n", | |
| "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from accelerate) (0.19.4)\n", | |
| "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from accelerate) (0.4.1)\n", | |
| "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.13.1)\n", | |
| "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (4.9.0)\n", | |
| "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (1.12)\n", | |
| "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.2.1)\n", | |
| "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1.2)\n", | |
| "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2023.6.0)\n", | |
| "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.1.0)\n", | |
| "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (2.31.0)\n", | |
| "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (4.66.1)\n", | |
| "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.3)\n", | |
| "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.3.2)\n", | |
| "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.6)\n", | |
| "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (2.0.7)\n", | |
| "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (2023.11.17)\n", | |
| "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n", | |
| "Requirement already satisfied: faiss-cpu in /usr/local/lib/python3.10/dist-packages (1.7.4)\n", | |
| "Collecting faiss-gpu\n", | |
| " Downloading faiss_gpu-1.7.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (85.5 MB)\n", | |
| "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m85.5/85.5 MB\u001b[0m \u001b[31m8.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", | |
| "\u001b[?25hInstalling collected packages: faiss-gpu\n", | |
| "Successfully installed faiss-gpu-1.7.2\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "application/vnd.colab-display-data+json": { | |
| "pip_warning": { | |
| "packages": [ | |
| "faiss" | |
| ] | |
| } | |
| } | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!mkdir -p 'data/paul_graham/'\n", | |
| "!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "50m7KoQtW6xN", | |
| "outputId": "10eeaf90-6d2f-4070-90d7-6520e108f8f7" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "--2023-12-24 01:44:38-- https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt\n", | |
| "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n", | |
| "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n", | |
| "HTTP request sent, awaiting response... 200 OK\n", | |
| "Length: 75042 (73K) [text/plain]\n", | |
| "Saving to: ‘data/paul_graham/paul_graham_essay.txt’\n", | |
| "\n", | |
| "\r data/paul 0%[ ] 0 --.-KB/s \rdata/paul_graham/pa 100%[===================>] 73.28K --.-KB/s in 0.01s \n", | |
| "\n", | |
| "2023-12-24 01:44:38 (6.03 MB/s) - ‘data/paul_graham/paul_graham_essay.txt’ saved [75042/75042]\n", | |
| "\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import os\n", | |
| "os.environ[\"OPENAI_API_KEY\"] = \"<open-api-key>\"" | |
| ], | |
| "metadata": { | |
| "id": "c4dSIDJqafeF" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Loading data in Faiss Vector store\n", | |
| "- Creating a Faiss Index\n", | |
| "- Load documents, build the VectorStoreIndex\n", | |
| "- Download and save data to Faiss store" | |
| ], | |
| "metadata": { | |
| "id": "xeSzxGqZY32X" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from llama_index import (\n", | |
| " SimpleDirectoryReader,\n", | |
| " load_index_from_storage,\n", | |
| " VectorStoreIndex,\n", | |
| " StorageContext,\n", | |
| ")\n", | |
| "from llama_index.vector_stores.faiss import FaissVectorStore\n", | |
| "from IPython.display import Markdown, display\n", | |
| "from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext\n", | |
| "from llama_index.llms import HuggingFaceLLM\n", | |
| "import torch\n", | |
| "import faiss\n", | |
| "\n", | |
| "# dimensions of text-ada-embedding-002\n", | |
| "d = 1536\n", | |
| "faiss_index = faiss.IndexFlatL2(d)\n", | |
| "\n" | |
| ], | |
| "metadata": { | |
| "id": "b_-VPqWAXAHa" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "\n", | |
| "# load documents\n", | |
| "documents = SimpleDirectoryReader(\"./data/paul_graham/\").load_data()\n", | |
| "vector_store = FaissVectorStore(faiss_index=faiss_index)\n", | |
| "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n", | |
| "index = VectorStoreIndex.from_documents(\n", | |
| " documents, storage_context=storage_context\n", | |
| ")\n", | |
| "# save index to disk\n", | |
| "index.storage_context.persist()\n" | |
| ], | |
| "metadata": { | |
| "id": "_4V0gXhRfVxW" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [], | |
| "metadata": { | |
| "id": "oIyftMvdfV2-" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [], | |
| "metadata": { | |
| "id": "2AVJt1xZfV6e" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Loading data from Faiss store" | |
| ], | |
| "metadata": { | |
| "id": "9fUKGYqvkVnJ" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "\n", | |
| "# load index from disk\n", | |
| "vector_store = FaissVectorStore.from_persist_dir(\"./storage\")\n", | |
| "storage_context = StorageContext.from_defaults(\n", | |
| " vector_store=vector_store, persist_dir=\"./storage\"\n", | |
| ")\n", | |
| "index = load_index_from_storage(storage_context=storage_context)" | |
| ], | |
| "metadata": { | |
| "id": "UlIx6-dIbUxW" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "\n" | |
| ], | |
| "metadata": { | |
| "id": "vs122vqGTsBW" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## General QA prompt with phi-2" | |
| ], | |
| "metadata": { | |
| "id": "yGANqwD8klRs" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from llama_index.prompts.prompts import SimpleInputPrompt\n", | |
| "\n", | |
| "system_prompt = \"You are a Q&A assistant. Your goal is to answer questions as accurately as possible based on the instructions and context provided.\"\n", | |
| "\n", | |
| "# This will wrap the default prompts that are internal to llama-index\n", | |
| "query_wrapper_prompt = SimpleInputPrompt(\"<|USER|>{query_str}<|ASSISTANT|>\")\n", | |
| "\n", | |
| "\n", | |
| "\n", | |
| "llm = HuggingFaceLLM(\n", | |
| " context_window=4096,\n", | |
| " max_new_tokens=256,\n", | |
| " generate_kwargs={\"temperature\": 0.0, \"do_sample\": False},\n", | |
| " system_prompt=system_prompt,\n", | |
| " query_wrapper_prompt=query_wrapper_prompt,\n", | |
| " tokenizer_name=\"microsoft/phi-2\",\n", | |
| " model_name=\"microsoft/phi-2\",\n", | |
| " device_map=\"cuda\",\n", | |
| " # uncomment this if using CUDA to reduce memory usage\n", | |
| " model_kwargs={\"torch_dtype\": torch.bfloat16}\n", | |
| ")\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 792, | |
| "referenced_widgets": [ | |
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| ] | |
| }, | |
| "id": "ReohpVquTmeE", | |
| "outputId": "a3d08819-cb7d-43f1-b18e-e88ba9b82d70" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "config.json: 0%| | 0.00/755 [00:00<?, ?B/s]" | |
| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "e2865427ea8f48958b39e81539f72798" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "The repository for microsoft/phi-2 contains custom code which must be executed to correctly load the model. You can inspect the repository content at https://hf.co/microsoft/phi-2.\n", | |
| "You can avoid this prompt in future by passing the argument `trust_remote_code=True`.\n", | |
| "\n", | |
| "Do you wish to run the custom code? [y/N] y\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "configuration_phi.py: 0%| | 0.00/2.03k [00:00<?, ?B/s]" | |
| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
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| "model_id": "60d9b1a7aa654854bb0e30c5826536ac" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "A new version of the following files was downloaded from https://huggingface.co/microsoft/phi-2:\n", | |
| "- configuration_phi.py\n", | |
| ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n" | |
| ] | |
| }, | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "The repository for microsoft/phi-2 contains custom code which must be executed to correctly load the model. You can inspect the repository content at https://hf.co/microsoft/phi-2.\n", | |
| "You can avoid this prompt in future by passing the argument `trust_remote_code=True`.\n", | |
| "\n", | |
| "Do you wish to run the custom code? [y/N] y\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
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| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "A new version of the following files was downloaded from https://huggingface.co/microsoft/phi-2:\n", | |
| "- modeling_phi.py\n", | |
| ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
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| "metadata": {} | |
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| "metadata": {} | |
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| { | |
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| "model_id": "eea47a45aa674aac86b7890d43bc57f6" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
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| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
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| ], | |
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| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "from llama_index.embeddings import HuggingFaceEmbedding\n", | |
| "\n", | |
| "# loads BAAI/bge-small-en\n", | |
| "# embed_model = HuggingFaceEmbedding()\n", | |
| "\n", | |
| "# loads BAAI/bge-small-en-v1.5\n", | |
| "embed_model = HuggingFaceEmbedding(model_name=\"BAAI/bge-small-en-v1.5\")\n", | |
| "\n", | |
| "service_context = ServiceContext.from_defaults(\n", | |
| " chunk_size=1024,\n", | |
| " llm=llm,\n", | |
| " embed_model=embed_model\n", | |
| ")\n", | |
| "\n" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 209, | |
| "referenced_widgets": [ | |
| "fcec2d4e50bd45ccbfdf39267a6ed133", | |
| "d82cdb8917704915a65afecff95255c2", | |
| "eb589b5c3e934fac90537a207575b2a4", | |
| "9623c5337790436a86d76f0a80227db8", | |
| "38257d819cff452596f3b27ace320809", | |
| "90f2501a597f48b6b92d643cd55fe929", | |
| "5440e65c34f64980b73665e968a97138", | |
| "4d156cf28edd4e59b32db2235df41885", | |
| "87844419d194495f96708ec6d807bdd1", | |
| "34ebb9f2fe9f46fa83aa2996a77409d3", | |
| "1820a3a7f36346dbaa6345bb235f1a48", | |
| "131be692694641608d9bbcfd7fc540f5", | |
| "e0383df6fb604542a6455c8f407989d0", | |
| "efde466d8b414e80bbf43266ccfaaff6", | |
| "b35b92a124a24f9a9d464c63a6aba552", | |
| "0cf1a72c738249f2b55a06e98c1003a5", | |
| "9c06ee330fee4377bc478b0b06766c9d", | |
| "36839428b905418ca140e5b3717d3a21", | |
| "13d1c94ecb5b43029cd354dc8baf6e0e", | |
| "fcf4736dd64e4536a3dc91b69bf77b2a", | |
| "03ffe88c2b96452aa7bc1fadc0189437", | |
| "c704d541ad2c4a4ab61072e41f72c8a7", | |
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| "278fe647ef7243b086608b00be445306", | |
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| "256c0dccaafd40c5aa4b1e5b1e894586", | |
| "f13df3643bb84d4a92a01c83b21631a1", | |
| "c91c0274363d4357978834eb7eca924d", | |
| "337b7985b8394e0e9a2346e2215b7ea8", | |
| "69d2dc5059ec4210a666e5f01e69bb47", | |
| "085cad3d1b12487291e3210a129ec812", | |
| "c833802cedea46ad8ba0ea08753cefd8", | |
| "47e686d692d14bee9ca8a50e2f51c478", | |
| "e738235c35ce42f9adbf927fec68f5d2", | |
| "8a8881055a324c2ebbe1c2da6a4c12cf", | |
| "08dcc49c7f944a9e88d5959578c16670", | |
| "9afe2b1576de4b2c8ac92c22957f9b07", | |
| "a13ab3863c654acfb4d6c3feb5595943", | |
| "f208937f5ee244e4a0fb6f55434cddee", | |
| "4eb9d35e623e48bda61dfb39cc568d2c", | |
| "477ba9cce20e49e3a09029ca83d85cab", | |
| "7cd7678d9c984970a329931012baa0c4", | |
| "c6cf85733c394939a6f918e8078ed20a", | |
| "eeb3ef464c704bb4a367b5e87ae5adcc", | |
| "af513fedd469461cbbd61b85b249d8b5", | |
| "e3bf05cd1c054c9fa0064de31f33ff91", | |
| "c4b3bc2f3f2f4e40af86360f13cc8a69", | |
| "da9c6b8cd3344b34b0770f0d213c8a6d", | |
| "281a15a401a1490fb95738ae45c28a11", | |
| "99b2ffbf14184bf5a819823a3236357a", | |
| "0e89b247116f41bc951963223bf366b8", | |
| "3b8a76b62d4c41a68d4aa5d57cc65229", | |
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| "1dd1294abc9e4e17847fd51ea8c2b35b", | |
| "87cf692d681e4d00bc0f86ed55f060f9" | |
| ] | |
| }, | |
| "id": "7x13lpwiTiXP", | |
| "outputId": "ff75443e-b536-40cd-aed3-dee165bef4cd" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "config.json: 0%| | 0.00/743 [00:00<?, ?B/s]" | |
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| "model_id": "fcec2d4e50bd45ccbfdf39267a6ed133" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
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| ], | |
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| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
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| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
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| "model_id": "db9422b3edab40229584f3d8c5d2c289" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "vocab.txt: 0%| | 0.00/232k [00:00<?, ?B/s]" | |
| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "e738235c35ce42f9adbf927fec68f5d2" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
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| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "af513fedd469461cbbd61b85b249d8b5" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
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| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "4604e2e5118e4c699a4343ceb7873492" | |
| } | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "index = VectorStoreIndex.from_documents(documents, service_context=service_context)\n", | |
| "\n", | |
| "query_engine = index.as_query_engine()\n", | |
| "\n", | |
| "def predict(input, history):\n", | |
| " response = query_engine.query(input)\n", | |
| " return str(response)\n" | |
| ], | |
| "metadata": { | |
| "id": "IlLCVBsbTdQ8" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "\n", | |
| "import gradio as gr\n", | |
| "\n", | |
| "gr.ChatInterface(predict).launch(share=True)" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 615 | |
| }, | |
| "id": "gZyvBS0STcQX", | |
| "outputId": "3378a7f8-6073-4596-cdb4-fdfdc294fcb6" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n", | |
| "Running on public URL: https://777cacaffb358d8108.gradio.live\n", | |
| "\n", | |
| "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ], | |
| "text/html": [ | |
| "<div><iframe src=\"https://777cacaffb358d8108.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>" | |
| ] | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 30 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [], | |
| "metadata": { | |
| "id": "UuixUCYtRpPE" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
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